Using Adobe Analytics New ‘Calculated Metrics’ to Fix Data Inaccuracies
Few features were more hotly anticipated following Adobe Summit than the arrival of the newly expanded calculated metrics to Adobe Analytics. Within one week of its release, it is already paying off big time for one of my clients. I’m going to share a use case for how these advanced calculated metrics fixed some pretty broken revenue data.
Our example for this case study is KittensSweaters.com*, an ecommerce business struggling with their Adobe Analytics data. Over the past few months, KittenSweaters has dealt with a number of issues with their revenue data, including:
- “Outlier” orders where the revenue recorded was grossly inflated or even negative
- A duplicate purchase event firing prior to the order confirmation page, that double counted revenue and
- Donations to their fundraiser counting as sweaters revenue, instead of in a separate event
For example, here you can see the huge outliers and negative revenue numbers they saw in their data:
Historically, this would require segmentation be layered upon all reports (and ensuring that all users knew to apply this segmentation before using the data!)
However, using the new Calculated Metrics in Adobe Analytics, KittenSweaters was able to create a corrected Revenue metric, and make it easily available to all users. Here’s how:
First, create a segment that is limited only to valid orders.
In the case of KittenSweaters, this segment only allows in orders where:
- The product category was “sweaters”; and
- The purchase was fired on the proper confirmation page; and
- The order was not one of the known “outlier” orders (identified by the Purchase ID)
You can test this segment by applying it on the current Revenue report and seeing if it fixes the issues. Historically, this would have been our only route to fix the revenue issues – layer our segment on top of the data. However, this requires all users to know about, and remember to apply, the segment.
So let’s go a step further and create our Calculated Metric (Components > Manage Calculated Metrics.)
Let’s call our new metric “Revenue (Corrected)”. To do so, drag your new segment of “Valid Sweater Orders” into the Definition of your metric, then drag the Revenue metric inside of the segment container. Now, the calculated metric will only report on Revenue where it matches that segment.
Voila! A quick “Share” and this metric is available to all KittenSweaters.com employees.
You can use this new metric in any report by clicking “Show Metrics” and adding it to the metrics displayed:
Now you’ll get to see the new Metrics Selector rather than the old, clunky pop-up. Select it from the list to populate your report. You can also select the default Revenue metric, to view the two side by side and see how your corrections have fixed the data.
You can quickly see that our new Revenue metric removes the outliers and negative values we saw in the default one, by correcting the underlying data. (YAY!)
You can even use these new calculated metrics in Report Builder! (Just be sure to download the newest version.)
It’s a happy day in the KittenSweaters office! While this doesn’t replace the need for IT to fix the underlying data, this definitely helps us more easily provide the necessary reporting to our executive team and make sure people are looking at the most accurate data.
Keep in mind one potential ‘gotcha’: If the segment underlying the calculated metric is edited, this will affect the calculated metric. This makes life easier while you’re busy building and testing your segment and calculated metric, but could have consequences if someone unknowingly edits the segment and affects the metric.
Share your cool uses of the new calculated metrics in the comments! If you haven’t had a chance to play around with them yet, check out this series of videos to learn more.
* Obviously KittenSweaters.com isn’t actually my client, but how puuuurrfect would it be if they were?!